Data Engineer Jobs

About The Position

Requirements

• At least 7 years of software engineering experience, including at least 3 years focused on data engineering, integration, platform, or infrastructure work.
• At least 2 years in a technical lead role, setting direction for shared work, mentoring engineers, and reviewing code and designs.
• Proficiency in Python, including the ability to read and write production-quality code.
• Strong SQL skills, including experience with large or complex datasets.
• Hands-on AWS experience with compute, storage, and at least one managed data service.
• Professional experience with AI-assisted development tools or coding agents, and curiosity about AI’s impact on engineering work.
• Ability to learn unfamiliar systems quickly and understand existing pipelines, tools, or codebases.
• Strong written communication skills.

Nice To Haves

• Experience with dbt and Snowflake.
• Experience with Apache Iceberg.
• Additional language proficiency, especially Spark or Java.
• Experience leading or coordinating engineering work across distributed or multi-location teams.
• Experience with ETL/ELT data pipelines, including schema management or data quality monitoring.
• Exposure to structured SQL and semi-structured JSON, Parquet, or Avro data at scale.
• Familiarity with analytics or ML platform tooling such as Airflow, MLflow, or SaaS equivalents.
• Azure or GCP experience.

Responsibilities

• Set technical direction for a small team of platform engineers and translate requirements and architecture guidance into well-scoped, sequenced work.
• Mentor engineers through pairing, code review, and design feedback, promoting quality, testing, and documentation standards.
• Coordinate delivery across contributors, including distributed team members, and surface risks and dependencies early.
• Remain a primary hands-on contributor to complex integration and platform work.
• Audit analytics applications to understand technology choices, data flows, and integration points.
• Design and implement integration patterns, such as APIs, event streams, and shared data contracts, to enable applications to interoperate without unnecessary rewrites.
• Build and maintain shared platform services, including authentication, observability, configuration management, and logging.
• Develop an understanding of existing data pipelines, including their sources, transformation logic, and dependencies.
• Partner with domain teams as an integration architect and collaborator, identifying opportunities to unify while deferring to domain expertise on data semantics and processing logic.
• Deploy and manage platform services on cloud infrastructure.
• Contribute to infrastructure-as-code practices and collaborate with the IT platform team on deployment pipelines and reliability standards.
• Construct evidence-based business cases for cloud feature adoption, translating technical needs into business value, risk reduction, and compliance considerations.

Benefits

• Medical coverage
• Dental coverage
• Vision coverage
• Other wellness programs
• Eligibility to participate in Huron’s annual incentive compensation program